Understanding and quantifying the inertia of power systems with the integration of converter-
interfaced generation (CIG) plays an essential role in the safe transition to a future low …

Online parameter estimation of permanent magnet synchronous machines is critical for
improving their control performance and operational reliability. This paper provides an …

Uncertainty quantification serves a central role for simulation-based analysis of physical,
engineering, and biological applications using mechanistic models. From a broad …

Permanent magnet synchronous motor (PMSM) drive has emerged as one of the most
preferred motor drives for industrial applications owing to its distinguished advantages, such …

This paper focuses on the benefits of adaptive control for permanent-magnet synchronous
machines; a novel method of online parameter estimation for such machines has been …

This paper proposes extended Kalman filtering (EKF) based real-time dynamic state and
parameter estimation using phasor measurement unit (PMU) data. In order to reduce …

Predictive mathematical models are a cornerstone of science and engineering. Yet
selecting, calibrating, and validating said science‐based models often remains an art in …

This paper deals with two topics from state and parameter estimation. The first contribution of
this work provides an overview of techniques used for determining which parameters of a …

This paper presents a new approach in estimating important parameters of power system
transient stability model such as inertia constant H and direct axis transient reactance xd'in …

Accurate load modeling is essential for power system dynamic simulation. In this paper, four
dynamic load models are identified based on multiple online measurement data from the …